Teaching

NA/ROB/MATH 599, PHY 590: Computational Symmetry in AI and Robotics

Joint Instructor, Graduate Course, University of Michigan

Offered: Fall 2024

Description: Symmetry describes the intrinsic structure and properties of a subject. In this course, we will explore the symmetries in geometry and rigorously express them in mathematics, covering relevant topics in group theory, differential geometry, representation theory, and Lie groups. Then, we will use them as tools to achieve computationally efficient and generalizable algorithms for learning, perception, estimation, and control with applications in many domains, such as AI, computer vision, and robotics. The course will cover novel topics in geometric learning and explores state of the art in symmetry-preserving and geometric learning methods.

NA 565, ROB 535, ME 599: Self-Driving Cars: Perception and Control

Joint Instructor, Graduate Course, University of Michigan

Offered: Fall 2023, Fall 2024

Description: Self-driving cars are a transformative technology for society. This course covers the underlying technologies in perception and control. Topics include deep learning, computer vision, sensor fusion, localization, trajectory optimization, obstacle avoidance, and vehicle dynamics. The course includes theoretical underpinnings of self-driving car algorithms and practical application of the material in hands-on labs.

NA/EECS 568, ROB 530: Mobile Robotics: Methods and Algorithms

Joint Instructor, Graduate Course, University of Michigan

Offered: Winter 2024

Description: Theory and application of probabilistic and geometric techniques for autonomous mobile robotics. This course presents and critically examines contemporary algorithms for robot perception. Topics include Bayesian filtering; stochastic representations of the environment; motion and sensor models for mobile robots; algorithms for mapping and localization; application to autonomous marine, ground, and air vehicles.